Glossary of Units of Measurement and Chemical Formulas

Transcription

1 Glossary of Units of Measurement and Chemical Formulas Units of Measurement ac af cm ds/m C EC Gt C/yr g gc/mj gc /m 2 /yr gkg 1 g/l ha hm 3 kg kg/m 3 km km 2 km 3 L m m 2 m 3 m 3 a 1 m 3 ha 1 m 3 /sec m 3 t 1 mi 2 Mm 3 μg/l μm acre acre-feet centimeter decisiemens per meter degree Celsius electrical conductivity gigaton of carbon per year gram gram of carbon per mega joule gram of carbon per meter square per year gram per kilogram gram per liter hectare cubic hectometer kilogram kilogram per cubic meter kilometer square kilometer cubic kilometer liter meter square meter cubic meter cubic meter per year cubic meter per hectare cubic meter per second cubic meter per ton square mile million cubic meters microgram per liter micrometer G. Schneier-Madanes, M.-F. Courel (eds.), Water and Sustainability in Arid Regions, DOI / _BM2, C Springer Science+Business Media B.V

2 334 Glossary of Units of Measurement and Chemical Formulas μmhos/cm mi mg mg/kg mg/l mm Mha Mha y 1 Mt y 1 mon Ngg 1 sec t yr micromhos per centimeter mile milligram milligram per kilogram milligrams per liter millimeter million hectares million hectares per year metric ton per year month nanogram per gram second ton year Chemical Formulas Cl F Fe +3 Mn +2 NO 2 NO 3 PO 3 4 SO 2 4 chloride fluoride iron (+3) cation manganese (+2) cation nitrite nitrate phosphate sulphate

3 Color Plates Plate 1 Study area location. (See also Fig. 2.1 on p. 18) 335

4 336 Color Plates Plate 2 Soil saline levels. (See also Fig. 2.4 on p. 27)

5 Color Plates 337 Plate 3 SSI (Soil Salinity Index) image calculated from the Landsat ETM+ image acquired on October 7, 2002, and photos showing the surface state of salt-affected soils in different parts of the study area. The class numbers correspond to the different degrees of salinity in ascending order. (See also Fig. 4.8 on p. 63)

6 338 Color Plates Plate 4 Classification image of Landsat MSS acquired on June 23, The classes from NDVI_class1 to NDVI_class7 were obtained by binning the NDVI values; higher class numbers indicate higher NDVI values and thus greater density and greenness of vegetation. (See also Fig. 4.9 on p. 66) Plate 5 Classification image of Landsat TM acquired on October 17, The classes from NDVI_class1 to NDVI_class7 were obtained by binning the NDVI values; higher class numbers indicate higher NDVI values and thus greater density and greenness of vegetation. (See also Fig on p. 66)

7 Color Plates 339 Plate 6 Classification image of Landsat ETM+ acquired on October 7, The classes from NDVI_class1 to NDVI_class7 were obtained by binning the NDVI values; higher class numbers indicate higher NDVI values and thus greater density and greenness of vegetation. (See also Fig on p. 67) Plate 7 SSI (Soil Salinity Index) calculated from Landsat ETM+ image acquired on October 7, Class numbers correspond to different degrees of salinity in ascending order. (See also Fig on p. 67)

8 340 Color Plates Plate 8 SSI (Soil Salinity Index) calculated from the image acquired on October 17, Class numbers correspond to the different degrees of salinity in ascending order. (See also Fig on p. 68) Plate 9 Dry areas of the world today (See also Fig. 7.5 on p. 111)

9 Color Plates 341 Plate 10 Precipitation anomalies (top: mm/day, bottom: %) calculated for the IPCC B2 scenario with the French CNRM model, comparing the averages for and Left: for December March. Right: for June September. (Source: Académie des Sciences 2006) (See also Fig. 7.6 on p. 112)

10 342 Color Plates Plate 11 Organization of the khettaras in central Haouz, west Marrakech. (Most of the seguias still run, while most khettaras are out of order) (Source: ORMVA Archives) (See also Fig on p. 156)

11 Color Plates 343 Plate 12 Organization of the khettaras in Tafilalet province. (Source: Thierry Ruf 2008, based on ORMVA-TF-SCET Plan directeur de mise en valeur agricole du Tafilalet Vol. No. 9, Rapport de synthèse) (See also Fig on p. 158)

12 344 Color Plates Plate 13 Population growth rates in the Southwest US (See also Fig on p. 222) Plate 14 The D1 and D2 curves used by the Rio Grande project (See also Fig on p. 233)

13 Color Plates 345 Plate 15 Visualizing groundwater pumping impacts (See also Fig on p. 235) Plate 16 Example of downscaled GCM projections for the US Southwest. The map to the left represents data at the GCM resolution. (Source: Cañon et al. 2008a) (See also Fig on p. 241)

14 346 Color Plates Plate 17 DSS results for 2010 and 2020 development scenarios. The arrows indicate the direction of change in riparian groundwater levels; the color of arrows indicates the magnitude of change. Red represents greater change, and green represents smaller change. (Source: Kang et al. 2009) (See also Fig on p. 241)

15 Index A Afforestation, 7 8, 13, 297, 298, 299, 304 Agriculture, 12, 55, 71, 76, 77 79, 80, 81, 84, 85, 88, 92, 95, 96, 97, 99, 100, 104, 105, 106, 107, 113, 114, 115, 118, 119, 166, 187, 208, 212, 214, 217, 227, 228, 234, 242, 249, 254, 261, 262, 266, 267, 276, 277, 279, 283, 287, 297, 314, 315, 316, 322, 323, 324, 325 Algeria, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 104, 151, 206, 212, 213, 214, 215, 216 Aquifer, 58, 76, 80, 88, 90, 91 92, 93, 94, 100, 105, 112, 118, 126, 128, 132, 135, 136, 209, 211, 213, 215, 222, 223, , 233, 242, 250, 276, 279, 281, 289, 304, 313, 314, 319 Archaeology, 54, Architecture, 166, 167, , 172, 174, 176 Argentina, 77, 78, 207, , 277, , 289 Arsenic, B Backpropagation neural model, 271 Blue water, 104, 107, 108, 110, 113, 208, 209, 212 Borderlands, C Chile, 127, 262, 263, 277, , 289 China, 3 13, 16, 17, 34, 35, 36, 40, 51 72, 78, 80, 117, 126, 140, 141, 147, 165, 182, 207, 315 Classifier, 20, Climate, 3, 7, 9, 17, 34, 35, 40, 44, 52, 54, 57, 61, 81, 82, 87, 88, 105, , 114, 116, 117, 119, 120, 126, 142, 158, 167, 168, 194, 205, 210, 227, 229, 230, , 246, 248, 249, 262, 263, 267, 278, 285, 296, 297, 299, 301, 304, 305, 312, 315, 319, 320, 327, 329 Compact, 129, 170, 227, 231, 232, 235, 326 Comprehensive water balance model, 108 Conchos, The, Conjunctive water management, Conservation, 4, 13, 19, 84, 99, 100, 106, 120, 171, 176, 197, 213, 216, 228, 229, 258, 298, 302, 303, 304, 314, 318, , 325 Contamination, 83, 100, 130, 250, , 280, 287, 289, 290, 297, 326 D Decision tree, 20, 24, 28, 29 Degradation, 4, 5, 6 7, 10, 12, 13, 16, 18, 54 57, 61, 62, 65, 70, 71, 76, 170, 278, , 301, 306 Dependency ratio, 210, 213 Desalinization, 93, 94 Desertification, 5 6, 8, 9, 11, 12, 13, 16, 34, 54, 55, 56, 65, 76, 80, 81, 82, 88, 100, 187, 191, 193, 300, 302, 312 Development, 4, 6, 7, 9 13, 36 38, 55, 68, 75, 81, 84, 85, 91, 92, 93, 94, 97, 99, 100, 107, 114, 116, 119, 120, , 147, 152, 153, 166, 176, 178, 191, 196, 213, 214, 216, , , 228, 229, 241, 246, 247, 249, 256, 257, 276, 285, 306, 312, 313, 314, 316, 317, 319, 320, 322, 323, 324, 325, 327, 346 Digital recording, 166 Drilling, 98, 135, 136, 157, 158, 159, 213, 224 Drought, 4, 35, 56, 79, 106, 111, 112, 113, , 119, 136, 157, 167, 186, 208, 223, , 230, 232, 234, 235, 238, 239, 242, 246, 248, 249, 257, 296, 304, 312, 315, 319, 324,

16 348 Index Drylands, 296, 297, 298, 299, 300, 302, 303, 304, 305, 306, 312, 313, 318, 320, 321, 322, 323, 324, 325 E Economic growth, 214, 246 Eco-reconstruction, 3 13 Ecotone, 28, 63, 65, 70 Edwards Aquifer, Efficiency, 10, 12, 35, 36, 37, 38, 39, 79, 84, 88, 100, 108, 110, 114, 115, 116, , 169, 174, 209, 224, 250, 251, 252, 253, 257, 288, 299, 320, 321, 325, 326, 328 Enclosure, 7, 8, 13, 167, 189, 197 ETM+ (Landsat Enhanced Thematic Mapper Plus), 18, 19, 21, 22, 23, 24, 27, 58, 59, 62, 63, 67 Evaluation, 228, 296, , 303, 304, 305, 306 F Foggara, 100, 126, 145, 151 Food (production, security, trade), 77, 104, , 108, 110, 114, 115, 116, 117, , 120, 217, 276, 312 Forecasts, 229, G Globalization, 316, 327 Great Man-Made Project, 94, 319 Greening project, 7 8 Green water, 104, 108, 109, 110, 113, 208, 212, 217 Groundwater, 6, 11, 12, 54, 56, 58, 59, 61, 62, 65, 69, 70, 76, 77, 78, 79 80, 82, 84, 89, 91, 92, 93, 94, 98, 100, 104, 105, 107, 126, 127, 128, 129, 130, 134, 135, 136, 142, 145, 146, 159, 209, 213, 221, 222, 223, , , 232, 234, 235, 236, 237, 241, 242, 249, 250, 276, 277, 278, 279, 281, 283, 284, 285, 297, 303, 313, 315, , 322, 328, 345, 346 H Health, 9, 16, 118, 120, 257, 275, 276, 277, 278, 281, 283, 284, 286, 296, 301, 302, 313, 314, 317, 322, 328 Heritage, 147, 157, I Inhabited space, , 173 Institution, 255 Institutional framework, Iran, 75 85, , 142, 145, 151, 209, 212, 216 Irrigation, 4, 6, 8, 11, 12, 18, 54, 56, 58, 61, 65, 69, 70, 71, 76, 77, 78, 79, 81, 82, 84, 96, 97, 99, 100, 101, 104, 105, 106, 107, 108, 109, 113, 114, 115, 118 K Kanerjing, 126, 141, 148 Karez, , 166 Karhunen Loeve Transform, Kashgar (Kashi), Keriya, 52, 57, 58, 59, 62, 65, 68, 69, 70, 71, 72, , 190, 191, 193, 195, 198, 199, 200 Khettara, 100, 126, , 342, 343 L Libya, 88, 91, 92, 93, 94, 95, 96, 97, 104, 212, 213, 214, 215, 216, 217, 319 Livestock, 70, 71, 96, 141, 187, 189, 277, 279, 282, 283, 302 Loggia, , 172, 174, 176, 177 M Maghreb, Maquiladora, 245, 246, 248 Marrakech, 151, 152, 153, 155, 156, 157, 158, 159, 160, 342 Mediterranean, 87, 88, 100, 104, 112, 126, MEI (Multivariate ENSO Index), 262, 267, 269, 270, 271, 272, 273 Mexico, 77, 78, 127, 207, 213, 218, 221, 222, 223, 225, 226, 227, 230, 232, 233, 234, 235, 236, 238, 242, , 283, 316, 317, 323, 326 Mining, 7, 11, 77, 83, 166, 213, 217, 276, 277, 284, 285 Morocco, 77, 78, 88, 89, 90, 94, 95, 96, 99, 100, 126, , 209, 216 N NDVI (Normalized Difference Vegetation Index), 15, 20, 21, 24, 26, 28, 38, 59, 60, 61, 65, 66, 67, 72, 338, 339 Net primary productivity (NPP), 34, 35, 37, 39, 40 44, 45, 46, 47, 48, 49 Neural network, 20, 262, Non-photosynthetic, 34 Non-renewable resources, 94, 206, 212, 217, 319

17 Index 349 O Oasis, 10, 11 13, 15 29, 34, 35, 40, 51 72, 137, 146, 152, 153, 157, 159, , , 214 Overgrazing, 5, 6, 7, 9, 65, 70, 72, 96 P Persia, 76, 77, 100, 125, 126, 127, 129, 139, 140, 142, 182, 321 Photosynthetic, 34, 35, 37, 38, 46 Pollution, 83, 88, 100, 107, 135, 166, 209, 210, 250, 313, 314 Prior appropriation, 222, , 238 Q Qanat, 80, 82, 100, , 139, 140, 145, 151, 209 R REACTION, , 303, 304 Reclamation, 7, 9, 10, 11, 61, 70, 125, 222, 226, 227, 323 Regression model, Remote sensing, 15 29, 33 49, 58, 61, 62, 64, 65, 71, 148, 200 Renewable resources (internal and external), 89, 134, 206, 211, 212, 213 Restoration, 47, 147, 200, Rio Grande Project, , 344 Riparian rights, 221, 224 S Sahara, 87, 88, 90, 91, 92, 104, 114, 115, 145, 154, 167, 206, 209, 213, 214, 215, 319 Salinization, 4, 5, 6, 10, 11, 12, 15 29, 34, 54, 55, 56, 61, 68, 69, 71, 72, 80 83, 93, 94, 105, 118, 314, 315 Salinized soil information, 19 28, 29 San Juan River Basin, Scarcity, 57, , , 129, 206, 217, 222, 250, 252, 287, 311, 312, 313 Shelterbelt, 8, 11, 12, 13, 298 Shortage thresholds, 209 Snowpack, 262, 263, 265, 267, 269, 270, 271, 272, 273, 329 Soil salinity index (SSI), 59, 61 64, 67, 68, 69, 70, 71, 72, 337, 339, 340 Southern Europe, 112, 296, 297, 298, 299, 307 Stormwater runoff, 323 Stream depletion, 223 Streamflow, 223, 225, 238, 239, 242, , 318 Surface water, 62, 63, 64, 65, 71, 77, 79, 81, 84, 89 91, 99, 104, 126, 134, 137, 146, 209, 221, 222, 223, 224, , , 234, 236, 242, 249, 279, 285, 313, 314, 315, 319, 320, 322 T Tafilalet, 151, 152, 153, 157, 158, 159, 162, 343 Taklimakan, 10, 17, 46, 51 72, , Tarim, 15 29, 35, 51, 52, 54, 56, 57, 65, 165, 166, 167, 182 Terrestrial ecosystem, 34, 35, 36, 39, 40 42, 43, 46 Tunisia, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, , 212, 215 Turnover, 248, 255, 257 Turpan, 45, 48, 52, U Urban growth, 248 Urban planning, 167, 169, 251 U.S. Southwest, , 248, 263, 329, 344, 345 Uygur, 51, 139, 145, 148, 166, 170, 171, 174, 176, 184, 187 V Vegetation, 3, 4, 6, 8, 9, 10, 11, 12, 16, 17, 19, 20, 21, 22, 24, 29, 34, 35, 36, 37, 38, 39, 40, 44, 46, 47, 56, 59, 60, 62, 64, 65, 66, 67, 68, 70, 71, 72, 112, 130, 167, 187, 188, 189, 191, 193, 196, 197, 297, 301, 303, 304, 305, 338, 339 Virtual water, 104, 106, 108, 109, 110, 113, 116, 119, 212, 214, 216, 217, 315, 325 W Wastewater, 76, 84, 95, 100, 104, 217, 234, 250, 251, 253, 256, 257, 313, 314, 318, Water budget, 296, 297, 300, , 305, 318, 322, 328 Water harvesting, 134, 137, 152, 299, , 323 Weather modification, 320 Wells, 79, 80, 91, 96, 100, 129, 130, 134, 135, 136, 137, 140, 141, 144, 147, 148, 159, 166, 167, 190, 209, 213, 232, , 249, 282, 283, 289 X Xinjiang, 4, 6, 8, 9, 10, 11, 13, 17, 18, 33 49, 51 53, 54 57, 139, 140, 141, 142, 144, 146, 147, 148, 169, 176, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 194, 195, 196, 199, 200